Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "57" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 33 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 33 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2460016 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 2.889441 | 0.058405 | 2.351723 | -0.803372 | 1.743507 | 0.207408 | -2.276976 | 1.422707 | 0.5962 | 0.6084 | 0.3424 | nan | nan |
| 2460015 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 3.086244 | -0.001468 | 2.421095 | -0.685295 | 1.915163 | 0.612855 | -2.303391 | 0.554983 | 0.6057 | 0.6187 | 0.3423 | nan | nan |
| 2460014 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 2.929146 | -0.342855 | 1.771522 | -0.209500 | 1.653706 | 0.991840 | -2.281199 | 0.694734 | 0.5870 | 0.5962 | 0.3469 | nan | nan |
| 2460013 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 2.711872 | 0.544381 | 2.218444 | -0.233987 | 1.407933 | 0.192725 | -2.501844 | 0.828718 | 0.6029 | 0.6189 | 0.3489 | nan | nan |
| 2460012 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 2.879035 | -0.037533 | 2.318464 | -0.984455 | 2.112321 | -0.011056 | -3.078797 | 0.797882 | 0.5935 | 0.6140 | 0.3491 | nan | nan |
| 2460011 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2460010 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2460009 | RF_maintenance | 100.00% | 99.95% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | 0.2846 | 0.0437 | 0.2666 | nan | nan |
| 2460008 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2460007 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459999 | RF_maintenance | 0.00% | 99.83% | 99.92% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.0916 | 0.1161 | 0.0474 | nan | nan |
| 2459998 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 2.973010 | 1.215537 | 2.546452 | -0.466869 | 2.243731 | 0.118230 | -1.935966 | 1.996560 | 0.6229 | 0.6350 | 0.3663 | nan | nan |
| 2459997 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 10.767745 | 1.847627 | 10.418166 | -0.795383 | 7.569517 | 1.463396 | 3.859707 | 4.648662 | 0.0468 | 0.6500 | 0.5054 | nan | nan |
| 2459996 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 11.445548 | 0.064834 | 12.439832 | -1.352550 | 7.133433 | -0.053126 | 1.144500 | 1.147852 | 0.0462 | 0.6593 | 0.5073 | nan | nan |
| 2459995 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 12.225398 | 0.057549 | 12.152405 | -1.192099 | 7.774518 | 1.284656 | 1.336384 | 3.125798 | 0.0500 | 0.6480 | 0.4906 | nan | nan |
| 2459994 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 11.660979 | -0.090319 | 10.501988 | -0.914582 | 7.605432 | 1.557173 | 1.049951 | 1.345185 | 0.0431 | 0.6388 | 0.4859 | nan | nan |
| 2459993 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459991 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 13.804931 | 2.785906 | 10.361347 | -1.033116 | 8.973035 | 1.813695 | 1.088087 | 2.361695 | 0.0417 | 0.6457 | 0.5002 | nan | nan |
| 2459990 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 10.644888 | 3.263774 | 9.649122 | -1.148455 | 8.913527 | 2.748463 | 3.144863 | 4.119446 | 0.0465 | 0.6473 | 0.5027 | nan | nan |
| 2459989 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 10.893699 | 0.299610 | 9.039056 | -0.759057 | 7.856688 | 1.103744 | 1.191794 | 1.642210 | 0.0410 | 0.6477 | 0.5079 | nan | nan |
| 2459988 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 158.723693 | 162.049650 | inf | inf | 3543.697381 | 3583.572275 | 4849.919570 | 4491.464230 | nan | nan | nan | nan | nan |
| 2459987 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 10.347093 | -0.553712 | 9.624468 | -1.371263 | 6.227019 | 0.066658 | 2.211597 | 1.668455 | 0.0468 | 0.6527 | 0.5066 | nan | nan |
| 2459986 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 13.525058 | 4.512502 | 11.104306 | -1.175580 | 9.198028 | 2.207488 | 6.160837 | 0.481759 | 0.0434 | 0.6723 | 0.5197 | nan | nan |
| 2459985 | RF_maintenance | 100.00% | 100.00% | 0.00% | 0.00% | - | - | 11.896002 | 0.391388 | 9.764767 | -1.404434 | 7.038797 | 0.066014 | 2.650349 | 2.721613 | 0.0442 | 0.6529 | 0.5137 | nan | nan |
| 2459984 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 31.434782 | 1.112166 | 5.189623 | -0.992873 | 15.865778 | 0.252637 | 0.915406 | 0.828341 | 0.4824 | 0.6708 | 0.3594 | nan | nan |
| 2459983 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 15.656880 | 0.112701 | 7.516793 | -1.255974 | 8.905839 | 2.705109 | 39.642933 | 0.840435 | 0.4765 | 0.6827 | 0.3712 | nan | nan |
| 2459982 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 16.060504 | 1.954920 | 6.431631 | -1.147268 | 2.180747 | 0.478341 | 0.954141 | -0.963687 | 0.4988 | 0.7171 | 0.3167 | nan | nan |
| 2459981 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 20.510168 | 3.388449 | 8.478218 | -1.361204 | 6.562876 | 6.270183 | 20.429393 | 5.055491 | 0.3897 | 0.6529 | 0.4099 | nan | nan |
| 2459980 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 18.925279 | 2.374640 | 6.726620 | 0.476719 | 5.160878 | 3.964926 | 4.382655 | 1.381846 | 0.5060 | 0.6909 | 0.3442 | nan | nan |
| 2459979 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 10.032795 | -0.209391 | 6.382285 | 0.491780 | 5.178716 | 1.358503 | 13.332628 | 1.396698 | 0.4755 | 0.6448 | 0.4127 | nan | nan |
| 2459978 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 18.021235 | 0.688330 | 7.493336 | 1.067744 | 5.882880 | 1.502398 | 36.124064 | 3.011911 | 0.4226 | 0.6447 | 0.4201 | nan | nan |
| 2459977 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 14.949078 | 0.596013 | 7.075623 | 1.087090 | 5.849993 | 3.493711 | 54.150121 | 7.587745 | 0.4272 | 0.6063 | 0.3823 | nan | nan |
| 2459976 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 12.875243 | 1.129622 | 7.032152 | 0.513009 | 4.530772 | 1.417863 | 40.678603 | 2.611964 | 0.4731 | 0.6513 | 0.4106 | nan | nan |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 2.889441 | 0.058405 | 2.889441 | -0.803372 | 2.351723 | 0.207408 | 1.743507 | 1.422707 | -2.276976 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 3.086244 | -0.001468 | 3.086244 | -0.685295 | 2.421095 | 0.612855 | 1.915163 | 0.554983 | -2.303391 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 2.929146 | 2.929146 | -0.342855 | 1.771522 | -0.209500 | 1.653706 | 0.991840 | -2.281199 | 0.694734 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 2.711872 | 2.711872 | 0.544381 | 2.218444 | -0.233987 | 1.407933 | 0.192725 | -2.501844 | 0.828718 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 2.879035 | 2.879035 | -0.037533 | 2.318464 | -0.984455 | 2.112321 | -0.011056 | -3.078797 | 0.797882 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 2.973010 | 2.973010 | 1.215537 | 2.546452 | -0.466869 | 2.243731 | 0.118230 | -1.935966 | 1.996560 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 10.767745 | 10.767745 | 1.847627 | 10.418166 | -0.795383 | 7.569517 | 1.463396 | 3.859707 | 4.648662 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Power | 12.439832 | 11.445548 | 0.064834 | 12.439832 | -1.352550 | 7.133433 | -0.053126 | 1.144500 | 1.147852 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 12.225398 | 12.225398 | 0.057549 | 12.152405 | -1.192099 | 7.774518 | 1.284656 | 1.336384 | 3.125798 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 11.660979 | 11.660979 | -0.090319 | 10.501988 | -0.914582 | 7.605432 | 1.557173 | 1.049951 | 1.345185 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 13.804931 | 13.804931 | 2.785906 | 10.361347 | -1.033116 | 8.973035 | 1.813695 | 1.088087 | 2.361695 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 10.644888 | 3.263774 | 10.644888 | -1.148455 | 9.649122 | 2.748463 | 8.913527 | 4.119446 | 3.144863 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 10.893699 | 0.299610 | 10.893699 | -0.759057 | 9.039056 | 1.103744 | 7.856688 | 1.642210 | 1.191794 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | nn Power | inf | 162.049650 | 158.723693 | inf | inf | 3583.572275 | 3543.697381 | 4491.464230 | 4849.919570 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 10.347093 | 10.347093 | -0.553712 | 9.624468 | -1.371263 | 6.227019 | 0.066658 | 2.211597 | 1.668455 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 13.525058 | 4.512502 | 13.525058 | -1.175580 | 11.104306 | 2.207488 | 9.198028 | 0.481759 | 6.160837 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 11.896002 | 0.391388 | 11.896002 | -1.404434 | 9.764767 | 0.066014 | 7.038797 | 2.721613 | 2.650349 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 31.434782 | 31.434782 | 1.112166 | 5.189623 | -0.992873 | 15.865778 | 0.252637 | 0.915406 | 0.828341 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Temporal Discontinuties | 39.642933 | 15.656880 | 0.112701 | 7.516793 | -1.255974 | 8.905839 | 2.705109 | 39.642933 | 0.840435 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 16.060504 | 16.060504 | 1.954920 | 6.431631 | -1.147268 | 2.180747 | 0.478341 | 0.954141 | -0.963687 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 20.510168 | 3.388449 | 20.510168 | -1.361204 | 8.478218 | 6.270183 | 6.562876 | 5.055491 | 20.429393 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Shape | 18.925279 | 2.374640 | 18.925279 | 0.476719 | 6.726620 | 3.964926 | 5.160878 | 1.381846 | 4.382655 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Temporal Discontinuties | 13.332628 | 10.032795 | -0.209391 | 6.382285 | 0.491780 | 5.178716 | 1.358503 | 13.332628 | 1.396698 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Temporal Discontinuties | 36.124064 | 0.688330 | 18.021235 | 1.067744 | 7.493336 | 1.502398 | 5.882880 | 3.011911 | 36.124064 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Temporal Discontinuties | 54.150121 | 14.949078 | 0.596013 | 7.075623 | 1.087090 | 5.849993 | 3.493711 | 54.150121 | 7.587745 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 57 | N04 | RF_maintenance | ee Temporal Discontinuties | 40.678603 | 1.129622 | 12.875243 | 0.513009 | 7.032152 | 1.417863 | 4.530772 | 2.611964 | 40.678603 |